Spectroscopy for a quantitative analysis of single component possibly in a solvent is based on simple linear regression using Beers' Law. This may be done by generating a calibration curve correlating the absorbance of the component at a specific wavelength with different concentrations of component in the solution. However, this approach does not work with multiple components, particularly if they have overlapping adsorption bands as seen in the Near Infrared Spectral region.
K. Norris of the Department of Agriculture of the United States of America demonstrated in 1968 the possibility of quantitative analysis using NIR spectra for complex mixtures. The technique was based on a multiple linear regression for NIR spectra (NIR-MLR). For example, the protein content of wheat flour (Cp) could be expressed as:Cp=K0+K1L(λ1)+K2L(λ2)+K3L(λ3)+where L(λn) represents the absorbance (or its derivative) at wavelength n. When an NIR spectra is taken the values for L(λn) are determined from the spectra. The wavelengths are selected to give a good regression fit to the calculation (e.g. minimize overlap and interference within the spectra). The regression coefficients K1 etc. are determined by a regression based on an analysis of calibration samples for known values. The model is then validated using different known samples from the calibration samples (validated regression coefficients).
The application of spectroscopy to process control has been known for a number of years. With the advent of high speed computers (microprocessors) spectra may be compared to a library of spectra for various products to determine how the process needs to be controlled/changed to produce a required product. This is not a regression approach but rather a direct comparison—closest fit approach to a known spectrum.
The analysis of light alkenes at high temperature and pressure has also been described by E. D. Yalvac et al.—Yalvac, E. D.; Seasholtz, M. B.; Beach, M. A.; Crouch, S. R.; Real-time analysis of light alkenes at elevated temperatures and pressures by fiber-optic near-infrared spectroscopy—Applied Spectroscopy, (1997), 51(10), 1565-1572, CODEN: APSPA4 ISSN:0003-7028, CAN 127:365507, AN 1997:694589, CAPLUS. In this publication, the real time analysis of light alkene mixtures (ethylene and 1-octene in Isopar E solvent) is discussed. The procedure involves generating a set of calibration spectra for which the composition is determined using a reference method. The experimental design includes a range of concentration, pressure and temperature for the application of interest. The calibration model is then utilized to predict new sample composition. The model predicts composition of mixture for which it was calibrated (i.e. only mixture of ethylene, 1-octene and isopar E). It does not mention the use of the model to measure ethylene and or 1-octene for mixture which include additional chemical component (polymer in a polymerization process).
IP.com publication identifier ‘IPCOM000134539D’ “NIR Process Monitoring” by Vela Estrada broadly discloses that NIR may be used to monitor chemical processes. The disclosure is quite broad but seems to be limited to direct measurement and control of a variable. For example to control catalyst one directly measures catalyst input or concentration in the reactor and makes appropriate modification to the catalyst flow rate. The reference does not seem to suggest measuring monomer concentration to control the flow of catalyst. Further the disclosure makes no reference to validating flow control systems on line.
U.S. Pat. No. 5,151,474 issued Sep. 29, 1992 to Lang et al. assigned to The Dow Chemical Company discloses the use of Fourier Transform Infrared Spectroscopy (FTIR) to control the manufacture of a polyolefin. The patent teaches the use of the infrared range of light rather than the near infrared. Adsorption measurements at 2120, 1909 and 1829 wavenumbers indicate the background signal and the concentration of ethylene and octene respectively. Based on these measurements the residual monomer content in the recycle stream is determined and the flow of monomers into the recycle stream is controlled to bring the feed stream to the set point for the process control. This is direct control measurement. The monomer concentration is measured and controlled. The patent does not suggest a regression analysis of the sample or the control nor the control by a different parameter.
U.S. Pat. No. 6,072,576 issued Jun. 6, 2000 to McDonald et al. assigned to Exxon Chemical Patents Inc., teaches a process to use on line NIR to control a halobutyl rubber reaction. In the process the instrumentation assembly 500 is mounted at the output of various stages of the reaction (Col. 3 lines 45-60). A number of sample spectra are generated and corrected for baseline error (eigenspectra) and error due to ex-sample chemical compounds present during the measurement process. For each eigenspectra a number of known properties or compositions of the polymer are determined. Then the components of the spectra relating to the property are given ratings or scores (dependent variables). The scores together with other data (viscosity and temperature) independent variables are used as constants in a process control algorithm. The process spectra are analyzed in similar manner to determine the dependent and independent variables which are compared to the process control algorithm. Then changes are made in the operation of the process to maintain the product at the desired specification. The present invention has eliminated the use of additional independent variables such as temperature and viscosity. The present invention does not require physical sample to be taken and analyzed to provide a reference property.
U.S. Pat. No. 6,864,331 issued Mar. 8, 2005, from an application filed Dec. 9, 2003, to Reimers at al. assigned to Fina Technology, Inc., teaches the use of NIR to control a process. Samples of product made in the reactor are analyzed for the desired property (e.g. styrene, polystyrene, diluents, mineral oil, rubber and rubber particle size—Col. 5 lines 60-65). In the present invention the calibration spectra are obtained without polymerization and without taking physical sample, while Reimers based his calibration curves on samples which are polymerized or partially polymerized (i.e. a direct measurement). The examples of Reimers suggest that for some samples a math pretreatment is applied to the spectra before regression (Col. 6 line 9 and 10) but for particle size the math pre treatment must not be used as it would dampen or negate the signal. The math pretreatment is a standard normal variant and a second derivative may be used. Reimers does not appear to be applying regression coefficients to a derivative of the sample spectra to get a value used in the process control.
In contrast to the above prior art one aspect of the present invention uses an indirect measurement of monomer concentration (NIR spectra) to which correlation factors are applied based on non polymerized mixtures of solvent and monomer to predict monomer conversion under polymerization condition. The correlation factor (regression model) is developed by taking NIR calibration spectra for a series of mixtures of solvent and monomers at pressure and temperature representative of polymerization conditions. The mixtures may be generated by varying the flow rates of the monomers feed rate in the process. The composition is calculated from the mass flow rate of the monomer in the process. The calibration spectra are collected using on-line measurements in the process stream. The spectra are mathematically treated to correct for baseline variation. A number of approaches are known for doing this. A preferred approach is to apply a Savitsky-Golay odd numbered window (e.g. 5 or 7 or 9) approach to smooth out the baseline or spectra (a first or second derivative may be used). The treated spectra are then subjected to a regression analysis to convert the spectra into a linear equation similar to that suggested by Norris. The regression method can be multiple linear regression (MLR), partial least square regression (PLS) or principal component regression (PCR). The regression method generates a set of coefficient, which can be applied to new sample spectra to obtain the monomer concentration (e.g. Monomerb concentration=b0+b1x1+b2x2+b3x3+ where bn is a regression coefficient and xn is the absorbance or derivative of the absorbance at a specific wavelength measured value).
The linear equation is verified against known samples and should have a low root mean square error of calibration (RMSEC) less than 2%, preferably significantly lower as determined by plotting calculated values (e.g. apply the same baseline correction, apply the same regression and insert the regression coefficients to provide a value) against known values (e.g. process flows etc.). The verified regression coefficients can then be directly applied to the unknown sample spectra (e.g. on line sample spectra) to determine a value (i.e. monomer(s) concentrations(s)). The value is converted to an indirect variable (e.g. monomer concentration is converted to conversion which is not measured) and the calculated conversion number is compared to a set point in the process control algorithm. None of the above art clearly expresses this subject matter.
The on-line NIR analyzer can also be utilized to verify the accuracy of process flow meters and identify process variations. For example, a calibration model can be generated using one monomer flow meter. A second flow meter can then be calibrated against the first one by comparing the predicted monomer composition versus the composition calculated form the second flow meter.
None of the above art suggest that NIR spectroscopy could be used to determine the validity of the calibration (or to recalibrate) the flow meters for a process.
U.S. Pat. No. 6,820,013 issued Nov. 16, 2004, from WO01/48458 published Jul. 5, 2001, to Frickel et al., assigned to Merk Patent GmbH, teaches a method and apparatus for the on line analysis of liquid mixtures by evaluation of binary mixtures. A library of the spectra of binary mixtures is prepared and used to evaluate the resulting mixtures. Contrary to Frickel a library or data base is not used in the present invention. Rather a series of tertiary mixtures of solvent and monomer (calibration samples) are analyzed and fitted to a linear function to provided correlation factors. These correlation factors are then applied directly to the sample spectra or portions of the sample spectra to indirectly determine a derivative value (conversion).
An additional advantage of the present invention is that the calculated correlation/regression factors are transferable among sites using the same or comparable processes. (e.g. solution to solution processes). So that the correlation factors may be calculated in a pilot scale facility but applied in commercial scale facility.
ASTM method E 1655-00 Standard Practices for Infrared Multivariate Quantative Analysis specifies at section 17.1.1 that the calibration samples must contain all chemical components which are expected to be present in the samples which are to be analyzed. Contrary to the approach of the ASTM the present invention successfully implements the use of calibration samples which do not contain all of the elements (i.e. polymer) in the calibration samples.
The present invention seeks to provide a method for process control in situations where direct measurement of a calibration value is difficult or not possible without the use of a library of spectra. Derivatives of the calibration spectra are used to generate a series of regression coefficients which are applied to a sample spectra to determine a direct value which is used to further determine an indirect or derivative value (conversion). The derivative value is compared to a set point for the process control and the process conditions are varied accordingly. This is a simple double derivative NIR process control process. Only solvent monomer mixtures are used to derive the regression coefficients factors applied to a NIR process sample to infer a secondary value which is used to modify a further secondary parameter to control the process.
The above process may also be used to verify the calibration of flow meters on line.
Additionally the process may also be used to determine the monomer concentration in the feed up stream of the reactors.